4.5 Article

Risdiplam: an investigational survival motor neuron 2 (SMN2) splicing modifier for spinal muscular atrophy (SMA)

期刊

EXPERT OPINION ON INVESTIGATIONAL DRUGS
卷 31, 期 5, 页码 451-461

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/13543784.2022.2056836

关键词

Central nervous system (CNS); neuromuscular disorders; risdiplam; RNA splicing modifier; SMN protein; SMN1 gene; SMN2 gene; spinal muscular atrophy (SMA)

资金

  1. Onassis Foundation [F ZQ 040-1/2020-2021]

向作者/读者索取更多资源

In this review, the authors critically evaluate the role of risdiplam in the treatment of spinal muscular atrophy (SMA). They provide an overview of the current market for SMA, discuss the mechanism of action and pharmacological properties of risdiplam, and present the results from phase 2/3 clinical trials. The authors conclude that risdiplam has shown efficacy and a satisfactory safety profile in pivotal trials for different types of SMA.
Introduction Spinal muscular atrophy (SMA) is a rare autosomal recessive neuromuscular disease which is characterised by muscle atrophy and early death in most patients. Risdiplam is the third overall and first oral drug approved for SMA with disease-modifying potential. Risdiplam acts as a survival motor neuron 2 (SMN2) pre-mRNA splicing modifier with satisfactory safety and efficacy profile. This review aims to critically appraise the place of risdiplam in the map of SMA therapeutics. Areas covered This review gives an overview of the current market for SMA and presents the mechanism of action and the pharmacological properties of risdiplam. It also outlines the development of risdiplam from early preclinical stages through to the most recently published results from phase 2/3 clinical trials. Risdiplam has proved its efficacy in pivotal trials for SMA Types 1, 2, and 3 with a satisfactory safety profile. Expert opinion In the absence of comparative data with the other two approved drugs, the role of risdiplam in the treatment algorithm of affected individuals is examined in three different patient populations based on the age and diagnosis method (newborn screening or clinical, symptom-driven diagnosis). Long-term data and real-world data will play a fundamental role in its future.

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